How to convert my tf.data.dataset into image and label arrays

I created a tf.data.dataset using the instructions on the keras.io documentation site.

dataset = tf.keras.preprocessing.image_dataset_from_directory( directory, labels="inferred", label_mode="int", class_names=None, color_mode="rgb", batch_size=32, image_size=(32,32), shuffle=True, )

My file directory is organized into classes with jpg files inside.

I don't know how to convert dataset file into and x_train and y_train to use in my model since model.fit doesn't take in the tf datasets.

I would appreciate some help in understanding how to take dataset and create x_train and y_train

Environment information
Windows 10,

Start with the keras.io documentation entry for image_dataset_from_directory and the model.fit entry point mentioned in the report. Determine whether the documentation clearly explains the expected dataset input and how it relates to x_train and y_train, then update the relevant guidance so the conversion workflow and completion criteria are unambiguous.